Bioinspired activation of silent synapses in layered materials for extensible neuromorphic computing

Activation of silent synapses is of great significance for the extension of neural plasticity related to learning and memory. Inspired by the activation of silent synapses via receptor insertion in neural synapses, we propose an efficient method for activating artificial synapses through the interca...

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Main Authors: Yan Kang, Yabo Chen, Yinlong Tan, Hao Hao, Cheng Li, Xiangnan Xie, Weihong Hua, Tian Jiang
Format: Article
Language:English
Published: Elsevier 2023-07-01
Series:Journal of Materiomics
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352847823000382
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author Yan Kang
Yabo Chen
Yinlong Tan
Hao Hao
Cheng Li
Xiangnan Xie
Weihong Hua
Tian Jiang
author_facet Yan Kang
Yabo Chen
Yinlong Tan
Hao Hao
Cheng Li
Xiangnan Xie
Weihong Hua
Tian Jiang
author_sort Yan Kang
collection DOAJ
description Activation of silent synapses is of great significance for the extension of neural plasticity related to learning and memory. Inspired by the activation of silent synapses via receptor insertion in neural synapses, we propose an efficient method for activating artificial synapses through the intercalation of Sn in layered α-MoO3. Sn intercalation is capable of switching on the response of layered α-MoO3 to the stimuli of visible and near infrared light by decreasing the bandgap. This mimics the receptor insertion process in silent neural synapses. The Sn-intercalated MoO3 (Sn-MoO3) exhibits persistent photoconductivity due to the donor impurity induced by Sn intercalation. This enables the two-terminal Sn-MoO3 device promising optoelectronic synapse with an ultrahigh paired pulse facilitation (PPF) up to 199.5%. On-demand activation and tunable synaptic plasticity endow the device great potentials for extensible neuromorphic computing. Superior performance of the extensible artificial neural network (ANN) based on the Sn-MoO3 synapses are demonstrated in pattern recognition. Impressively, the recognition accuracy increases from 89.7% to 94.8% by activating more nodes into the ANN. This is consistent with the recognition process of physical neural network during brain development. The intercalation engineering of MoO3 may provide inspirations for the design of high-performance neuromorphic computing architectures.
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spelling doaj.art-f1d9c6c845fb42ad99ec90e040967f802023-07-11T04:06:29ZengElsevierJournal of Materiomics2352-84782023-07-0194787797Bioinspired activation of silent synapses in layered materials for extensible neuromorphic computingYan Kang0Yabo Chen1Yinlong Tan2Hao Hao3Cheng Li4Xiangnan Xie5Weihong Hua6Tian Jiang7College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha, 410073, ChinaInstitute for Quantum Information & State Key Laboratory of High Performance, Computing College of Computer, National University of Defense Technology, Changsha, 410073, ChinaCollege of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha, 410073, China; Corresponding author.Institute for Quantum Science and Technology, College of Science, National University of Defense Technology, Changsha, 410073, ChinaInstitute for Quantum Science and Technology, College of Science, National University of Defense Technology, Changsha, 410073, ChinaInstitute for Quantum Science and Technology, College of Science, National University of Defense Technology, Changsha, 410073, ChinaCollege of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha, 410073, China; Corresponding author.Institute for Quantum Science and Technology, College of Science, National University of Defense Technology, Changsha, 410073, China; Corresponding author.Activation of silent synapses is of great significance for the extension of neural plasticity related to learning and memory. Inspired by the activation of silent synapses via receptor insertion in neural synapses, we propose an efficient method for activating artificial synapses through the intercalation of Sn in layered α-MoO3. Sn intercalation is capable of switching on the response of layered α-MoO3 to the stimuli of visible and near infrared light by decreasing the bandgap. This mimics the receptor insertion process in silent neural synapses. The Sn-intercalated MoO3 (Sn-MoO3) exhibits persistent photoconductivity due to the donor impurity induced by Sn intercalation. This enables the two-terminal Sn-MoO3 device promising optoelectronic synapse with an ultrahigh paired pulse facilitation (PPF) up to 199.5%. On-demand activation and tunable synaptic plasticity endow the device great potentials for extensible neuromorphic computing. Superior performance of the extensible artificial neural network (ANN) based on the Sn-MoO3 synapses are demonstrated in pattern recognition. Impressively, the recognition accuracy increases from 89.7% to 94.8% by activating more nodes into the ANN. This is consistent with the recognition process of physical neural network during brain development. The intercalation engineering of MoO3 may provide inspirations for the design of high-performance neuromorphic computing architectures.http://www.sciencedirect.com/science/article/pii/S2352847823000382Activation of silent synapseIntercalationLayered materialsNeuromorphic computing
spellingShingle Yan Kang
Yabo Chen
Yinlong Tan
Hao Hao
Cheng Li
Xiangnan Xie
Weihong Hua
Tian Jiang
Bioinspired activation of silent synapses in layered materials for extensible neuromorphic computing
Journal of Materiomics
Activation of silent synapse
Intercalation
Layered materials
Neuromorphic computing
title Bioinspired activation of silent synapses in layered materials for extensible neuromorphic computing
title_full Bioinspired activation of silent synapses in layered materials for extensible neuromorphic computing
title_fullStr Bioinspired activation of silent synapses in layered materials for extensible neuromorphic computing
title_full_unstemmed Bioinspired activation of silent synapses in layered materials for extensible neuromorphic computing
title_short Bioinspired activation of silent synapses in layered materials for extensible neuromorphic computing
title_sort bioinspired activation of silent synapses in layered materials for extensible neuromorphic computing
topic Activation of silent synapse
Intercalation
Layered materials
Neuromorphic computing
url http://www.sciencedirect.com/science/article/pii/S2352847823000382
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